Sparsity: meaning, definitions and examples
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sparsity
[ ˈspɑːsɪti ]
in statistics
Sparsity refers to the property of having very few non-zero elements in a dataset or mathematical structure. It is commonly used in the context of sparse matrices, where most of the elements are zero.
Synonyms
infrequency, rareness, scantiness
Examples of usage
- The sparsity of the data matrix allowed for efficient storage and computation.
- Sparse coding techniques take advantage of the sparsity present in the data.
in everyday language
Sparsity can refer to a state of being scarce or lacking in quantity. It often implies a sense of insufficiency or inadequacy.
Synonyms
Examples of usage
- The sparsity of resources in the region led to widespread poverty.
- The sparsity of options left us with limited choices.
Translations
Translations of the word "sparsity" in other languages:
🇵🇹 esparsidade
🇮🇳 विरलता
🇩🇪 Sparsamkeit
- Dürre
- Mangel
🇮🇩 kekurangan
🇺🇦 рідкість
🇵🇱 rzadkość
🇯🇵 希薄
🇫🇷 rareté
🇪🇸 escasez
🇹🇷 seyreklik
🇰🇷 희소성
🇸🇦 ندرة
🇨🇿 řidkost
🇸🇰 riedkosť
🇨🇳 稀疏
🇸🇮 redkost
🇮🇸 fámenni
🇰🇿 тапшыдық
🇬🇪 ნაკლებობა
🇦🇿 nadirlik
🇲🇽 escasez
Word origin
The word 'sparsity' originated from the Latin word 'sparsum', which means scattered. It has been used in mathematics and statistics to describe datasets with a low density of non-zero elements. The concept of sparsity has gained importance in various fields such as machine learning, signal processing, and optimization.